OBJECTIVE: To investigate practical and methodological problems in assessing the quality of care of multiple conditions in general practice. SETTING: Sixteen general practices from two socioeconomically diverse regions in the UK. METHOD: Quality of care was assessed in 100 randomly selected patient records in each practice using an established set of quality indicators covering 23 conditions commonly seen in primary care. Inter-rater reliability assessment was carried out for five of the conditions. RESULTS: Conducting simultaneous quality assessment across multiple conditions is highly resource intensive. Poor data quality and the low prevalence of some items of care defined by the indicators are significant problems. Scores for individual indicators require very large samples for reliable assessment. Quality scores are more reliable when reported at a higher unit of analysis. This is particularly true for indicators and conditions with low prevalence where data may need to be aggregated to the level of groups of conditions or organisational providers. There is no single ideal way of aggregating quality scores. CONCLUSION: The study identified some of the practical and methodological difficulties in assessing quality of care across multiple conditions. For improved quality assessment, advances in information technology and improvements in data quality are required for more efficient and reliable data extraction from medical records, together with the development of methods for combining scores across indicators, conditions, and practices. However, electronic data extraction methods will still be based on the assumption that the care recorded reflects the care provided.
OBJECTIVE: To investigate practical and methodological problems in assessing the quality of care of multiple conditions in general practice. SETTING: Sixteen general practices from two socioeconomically diverse regions in the UK. METHOD: Quality of care was assessed in 100 randomly selected patient records in each practice using an established set of quality indicators covering 23 conditions commonly seen in primary care. Inter-rater reliability assessment was carried out for five of the conditions. RESULTS: Conducting simultaneous quality assessment across multiple conditions is highly resource intensive. Poor data quality and the low prevalence of some items of care defined by the indicators are significant problems. Scores for individual indicators require very large samples for reliable assessment. Quality scores are more reliable when reported at a higher unit of analysis. This is particularly true for indicators and conditions with low prevalence where data may need to be aggregated to the level of groups of conditions or organisational providers. There is no single ideal way of aggregating quality scores. CONCLUSION: The study identified some of the practical and methodological difficulties in assessing quality of care across multiple conditions. For improved quality assessment, advances in information technology and improvements in data quality are required for more efficient and reliable data extraction from medical records, together with the development of methods for combining scores across indicators, conditions, and practices. However, electronic data extraction methods will still be based on the assumption that the care recorded reflects the care provided.
Authors: Sabine Ludt; Stephen M Campbell; Jan van Lieshout; Richard Grol; Joachim Szecsenyi; Michel Wensing Journal: BMC Health Serv Res Date: 2011-04-07 Impact factor: 2.655
Authors: Sabine Ludt; Stephen M Campbell; Davorina Petek; Justine Rochon; Joachim Szecsenyi; Jan van Lieshout; Michel Wensing; Dominik Ose Journal: Implement Sci Date: 2013-03-09 Impact factor: 7.327